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Joint Optimization of Unrelated Parallel Machine Scheduling and Multi-Trips Vehicle Routing with Time Windows

In: Technological Innovations for Sustainable Development

Author

Listed:
  • Hind Bouifalioune

    (Moulay Ismaïl University)

  • Majda Fikri

    (Ibn Zohr University)

  • Ghizlane Bencheikh

    (Moulay Ismaïl University)

Abstract

This study examines the difficulties of synchronizing production and distribution scheduling, with a particular focus on the Unrelated Parallel Machine Scheduling Problem (UPMSP) in production and the Multi-Trip Vehicle Routing Problem (VRP) in distribution. The objective is to minimize the makespan, total weighted tardiness, and transportation costs, while ensuring efficient batch deliveries using a fleet of homogeneous-capacity vehicles. To tackle this complex problem, we formulate a Mixed-Integer Nonlinear Programming (MINLP) model and propose a Genetic Algorithm (GA) as a solution approach. Since no established benchmarks exist for this specific problem, we evaluate the performance of our GA by comparing its solutions against IBM CPLEX, a state-of-the-art exact solver. The comparison focuses on small-scale instances generated in this study. Results indicate that the proposed GA is capable of reaching optimal solutions for most small-sized instances, demonstrating its effectiveness in solving this challenging integrated scheduling problem.

Suggested Citation

  • Hind Bouifalioune & Majda Fikri & Ghizlane Bencheikh, 2025. "Joint Optimization of Unrelated Parallel Machine Scheduling and Multi-Trips Vehicle Routing with Time Windows," Lecture Notes in Information Systems and Organization, in: Badr-Eddine Boudriki Semlali & Ikram Ben Abdel Ouahab & Fabio Angeletti (ed.), Technological Innovations for Sustainable Development, pages 451-464, Springer.
    • Handle: RePEc:spr:lnichp:978-3-032-06725-8_38
    DOI: 10.1007/978-3-032-06725-8_38
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